Digital photographs are often of reduced quality because of corruption by any one or more of a number of noise sources. For example, sensor noise, motion blur due to movement of the camera or subject during the exposure time, occlusion due to dust, optical low pass filtering, chromatic aberration, compression and quantization artifacts, down sampling and other sources of noise.
Existing digital image restoration processes aim to improve image quality by processing digital images to remove effects of the noise sources. For example, statistical models of natural images and imaging systems may be used to try to remove the effects of noise sources. There is an ongoing desire to improve digital image restoration processes both to improve quality of the output images and to reduce the costs involved (time costs, resource costs, usability and other costs).
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known image restoration processes and equipment.